Saudi Arabia's infrastructure expansion requires assurance systems that match the speed, complexity, and sustainability expectations of Vision 2030. This review examines how automated inspection, digitally enabled calibration, and metrological traceability can be integrated into a coherent quality architecture for infrastructure delivery. The literature indicates that computer vision, uncrewed aerial vehicles, laser scanning, structural health monitoring and digital twins can accelerate defect detection and condition assessment. Still, their decisions remain trustworthy only when the underlying measurements, sensor states, and uncertainty information are traceable. Digital calibration certificates provide a machine-readable mechanism to carry calibration status, uncertainty, and provenance into automated workflows. In contrast, BIM and digital twins provide the asset context needed to convert measurements into engineering decisions. Evidence from construction and asset-management research further shows that automation is not intrinsically sustainable: benefits depend on interoperability, cybersecurity, competence, data governance, risk-based human oversight, and lifecycle use of verified data. The review develops an integrated traceability-to-decision framework for Saudi infrastructure projects, linking calibrated sensing, automated inspection, digital evidence, engineering acceptance and lifecycle feedback. It argues that traceability should be treated as digital infrastructure rather than a laboratory back-office function. It proposes research and policy priorities for scalable implementation across giga-projects, transport, utilities and public assets.